Special Issue

Topic: Post-Quantum Cryptography and AI Privacy (PQAP)
A Special Issue of Journal of Surveillance, Security and Safety
ISSN 2694-1015 (Online)
Submission deadline: 20 Dec 2022
Guest Editor(s)
Special Issue Introduction
Security is currently undergoing a major transformation. When quantum computing is realized, conventional security technologies will not be able to provide confidentiality, integrity, and availability. It is believed that it will no longer be possible to achieve this goal. Since we are in the stage from conventional cryptography to post-quantum cryptography, it is important to study ordinary cryptography as well. As for other challenges, with the progress of digitization, it is important to build secure and privacy-protected applications using smart contracts, etc. Finally, with the importance and spread of AI, it is important to consider not only the privacy and security of data alone, but also the privacy and security of data used in AI. This Special Issue of Journal of Surveillance, Security, and Safety aims to research the state-of-the-art developments, conceptual, theory, design, implementation, and evaluation from Post-quantum Cryptography to privacy and security to AI. Authors are invited to submit original practical work and survey papers. Areas of interest for this special journal issue include, but are not limited to, the following topics:
● Post-quantum security
● Public-key encryption
● Digital signature and message authentication codes
● Applied cryptography
● Cryptographic protocols
● Indistinguishability obfuscation in cryptography
● Attack identification and adversarial defense methods in IoT
● Applications of AI technologies for enhancing security and privacy
● Cyber security for future IoT technology
● Privacy issues in AI
● Security and privacy protection for AI on mobile devices
● Defense against training data pollution attacks
● Data sanity checks to improve the quality of learning samples
● Data analysis over encrypted/perturbed data
● Secure distributed processing of tokenized data
● Privacy-preserving techniques in data collection
● Algorithms for information fusion over data from unreliable sources
● Security and privacy related to NFTs, smart contracts and blockchain technology in general
● Post-quantum security
● Public-key encryption
● Digital signature and message authentication codes
● Applied cryptography
● Cryptographic protocols
● Indistinguishability obfuscation in cryptography
● Attack identification and adversarial defense methods in IoT
● Applications of AI technologies for enhancing security and privacy
● Cyber security for future IoT technology
● Privacy issues in AI
● Security and privacy protection for AI on mobile devices
● Defense against training data pollution attacks
● Data sanity checks to improve the quality of learning samples
● Data analysis over encrypted/perturbed data
● Secure distributed processing of tokenized data
● Privacy-preserving techniques in data collection
● Algorithms for information fusion over data from unreliable sources
● Security and privacy related to NFTs, smart contracts and blockchain technology in general
Submission Deadline
20 Dec 2022
Submission Information
For Author Instructions, please refer to https://oaepublish.com/jsss/author_instructions
For Online Submission, please login at https://oaemesas.com/login?JournalId=jsss&SpecialIssueId=jsss220414
Submission Deadline: 20 Dec 2022
Contacts: Esther Cao, Assistant Editor, JSSS-editor@oaemesas.com
Published Articles
Open Access Original Article
Graph neural network based function call graph embedding for malware classification
This article belongs to the Special Issue Post-Quantum Cryptography and AI Privacy (PQAP)
J Surveill Secur Saf 2023;4:47-61.
Available online: 29 Jun 2023